Rules-based incentives promise fairness, but they quietly reward the lucky. Two disciplines help supervisory boards tell the difference.
A record year earns a record bonus, and the boardroom feels certain it is rewarding merit. But in any environment with real uncertainty, a strong result can follow a weak process that got lucky, and a sound process can produce a poor result because conditions turned. Reward the outcome, and you often reward the luck.
Why rules-based incentives don’t fix it
The leakage from luck into pay is well documented. In a classic study of CEO compensation, Marianne Bertrand and Sendhil Mullainathan found that pay rose about as much on a windfall dollar the executive could not have produced as on a dollar they plausibly earned. The effect shrank where governance was strong: each additional large shareholder on the board cut the pay-for-luck by roughly a third.
One response is to make evaluation mechanical, with fixed metrics, pre-agreed targets and transparent formulas. Those rules go in the right direction and are easy to defend to shareholders. Yet they still incorporate flaws. First, they reward the outcome rather than the quality of the decision behind it, a pattern psychologists have called outcome bias since the 1980s: we rate a choice as good because it worked out, even when we know the reasoning was weak. Second, more metrics do not reliably mean better pay-for-performance. Across the S&P 1500, ISS-Corporate reports that adding metrics to short-term plans goes hand in hand with higher payouts but not with stronger shareholder returns. Third, targets tend to move in one direction. When oil and gas prices collapsed in 2020, Kimmeridge documented boards softening targets for their exploration-and-production executives, while the reverse adjustment, raising the bar when conditions turned favorable, rarely happened.
Establishing operational peer metrics while considering the mandate
The way forward is not to abandon metrics but to add two elements to separate what a person controlled from what the market handed them.
Take a management board member who posts record earnings during a sector-wide tailwind: falling rates, a demand surge, a commodity swing. Rewarding the headline number rewards the weather. The sharper test is peer-relative: did competitors in the same conditions do as well, or better? Benchmarking against a peer group strips out the shared tailwind and isolates what the individual added. The logic is already familiar in the form of relative total shareholder return; the point is to apply it below the share price, to the operating results boards actually judge.
Mandate matters just as much as market. Picture two directors who each grow their unit’s profit by ten percent. One inherited a business already expanding in a buoyant segment, where ten percent may understate the opportunity; the other was handed a turnaround in a shrinking market, where ten percent was wrung from nothing. The identical headline conceals opposite achievements. The honest measure is not the absolute result but attainment relative to what the mandate made possible. AI could, in principle, help here: regressing a unit’s results on sector and macro drivers and treating the residual as the controllable part.
Calibrating the review
People judge their own performance poorly, and the bias is self-serving: analyzing fund managers’ shareholder reports, Wang (2024) found managers roughly 41% more likely to credit their own decisions for what helped returns than to blame them for what hurt
Calibrating the review can be achieved by collecting two independent estimates beforehand: the member’s self-rating and the aggregated view of their direct reports, who see execution quality the board never observes. A large positive gap, where the executive rates themselves well above their team, is the pattern most strongly linked to leadership derailment and warrants a closer look; a negative gap may point to an under-recognized contribution the board is not seeing. The mechanisms it draws on, such as relative performance evaluation, 360-degree feedback, and calibration meetings, are established. The gap should prompt inquiry and serve as a basis for learning
Two changes before the next cycle
First, read every headline number against two benchmarks: what comparable rivals achieved, and what the mandate made realistically possible. If a review cannot say what the executive added beyond what the market delivered, it has not yet measured merit.
Second, collect two estimates and examine the gap, not the average. Rules-based pay is worth keeping. Taking its output as the final word is the mistake. Boards that reward how well the game was played, rather than how the ball happened to bounce, give themselves the best chance of holding on to their strongest people and of not overpaying the merely fortunate.
A four-question review template
1. What did peers in the same conditions achieve? (strip out the shared tailwind)
2. What did the mandate make possible? (judge attainment against the realistic range, set at the start of the term)
3. Where is the gap between the self-rating and the aggregated view of direct reports — and in which direction?
4. Was the decision process sound given what was knowable at the time — independent of how it turned out?
Written by Christoph Burger.
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